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Introduction

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Sentic Computing

Part of the book series: SpringerBriefs in Cognitive Computation ((BRIEFSCC,volume 2))

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Abstract

In a world in which millions of people express their opinions about commercial products in blogs, wikis, forums, chats, and social networks, the distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand, or organisation. The automatic analysis of online opinions, however, involves a deep understanding of natural language text by machines, from which we are still very far. Online information retrieval, in fact, is still mainly based on algorithms relying on the textual representation of web pages. Such algorithms are very good at retrieving texts, splitting them into parts, checking the spelling, and counting their words. But when it comes to interpreting sentences and extracting useful information for users, their capabilities are still very limited.

We can understand almost anything, but we can’t understand how we understand Albert Einstein.

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Notes

  1. 1.

    http://epinions.com

  2. 2.

    http://yelp.com

  3. 3.

    http://rateitall.com

  4. 4.

    http://twitter.com

  5. 5.

    http://livejournal.com

  6. 6.

    http://patientopinion.org.uk

  7. 7.

    http://wordnet.princeton.edu

  8. 8.

    http://conceptnet5.media.mit.edu

  9. 9.

    http://research.microsoft.com/probase

  10. 10.

    http://bing.com

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Authors and Affiliations

  1. Media Laboratory, Massachusetts Institute of Technology, Cambridge, USA

    Erik Cambria

  2. Department of Computing Science, University of Stirling, Stirling, UK

    Amir Hussain

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  1. Erik Cambria
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  2. Amir Hussain
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Correspondence to Erik Cambria .

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Cambria, E., Hussain, A. (2012). Introduction. In: Sentic Computing. SpringerBriefs in Cognitive Computation, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5070-8_1

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